Abstract:The optimization of irrigation use in agriculture is a key challenge to increase farm profitability and reduce its ecological footprint. To this context, an understanding of more efficient irrigation systems includes the assessment of water redistribution at the microscale. This study aimed to investigate rainfall interception by maize canopy and to model the soil water dynamics at row scale as a result of rain and sprinkler irrigation with HYDRUS 2D/3D. On average, 78% of rainfall below the maize canopy was intercepted by the leaves and transferred along the stem (stemflow), while only 22% reached the ground directly (throughfall). In addition, redistribution of the water with respect to the amount (both rain and irrigation) showed that the stemflow/throughfall ratio decreased logarithmically at increasing values of incident rainfall, suggesting the plant capacity to confine the water close to the roots and diminish water stress conditions. This was also underlined by higher soil moisture values observed in the row than in the inter-row at decreasing rainfall events. Modelled data highlighted different behavior in terms of soil water dynamics between simulated irrigation water distributions, although they did not show significant changes in terms of crop water use efficiency. These results were most likely affected by the soil type (silty-loam) where the experiment was conducted, as it had unfavorable physical conditions for the rapid vertical water movement that would have increased infiltration and drainage. OPEN ACCESSWater 2015, 7 2255
The surface energy balance algorithm for land (SEBAL) has been successfully applied to estimate evapotranspiration (ET) and yield at different spatial scales. However, ET and yield patterns have never been investigated under highly heterogeneous conditions. We applied SEBAL in a salt-affected and water-stressed maize field located at the margin of the Venice Lagoon, Italy, using Landsat images. SEBAL results were compared with estimates of evapotranspiration by the Food and Agriculture Organization (FAO) method (ET c ) and three-dimensional soil-plant simulations. The biomass production routine in SEBAL was then tested using spatially distributed crop yield measurements and the outcomes of a soil-plant numerical model. The results show good agreement between SEBAL evapotranspiration and ET c . Instantaneous ET simulated by SEBAL is also consistent with the soil-plant model results (R 2 = 0.7047 for 2011 and R 2 = 0.6689 for 2012). Conversely, yield predictions (6.4 t/ha in 2011 and 3.47 t/ha in 2012) are in good agreement with observations (8.64 t/ha and 3.86 t/ha, respectively) only in 2012 and the comparison with soil-plant simulations (8.69 t/ha and 5.49 t/ha) is poor. In general, SEBAL underestimates land productivity in contrast to the soil-plant model that overestimates yield in dry years. SEBAL provides accurate predictions under stress conditions due to the fact that it does not require knowledge of the soil/root characteristics.crop-specific relations between ET and yield [6,7], it provides a measure of both water demand and land productivity. Yield is thus the ultimate indicator to describe crop response to water resource management [8] and the quantification of field scale ET is fundamental for managers to maximize land productivity while minimizing water losses [9][10][11]. Crop yield is also a key element for rural development and national food security. For these reasons, forecasting crop yield a few months before harvest can be of paramount importance for timely initiation of the food trade, securing national demand, and organizing food transport within countries [6,7,12].The yield of many agricultural crops is generally predicted from the amount of water used by the crop, i.e., ET [6,7]. Traditionally, ET from fields has been estimated according to the Food and Agriculture Organization (FAO) method [13], i.e., by multiplying a weather-based reference ET 0 by a crop coefficient (K c ) determined according to crop type and growth stage. However, the suitability of the idealized K c coefficient to describe the actual vegetative and growing conditions, especially in water limited areas, was questioned by many authors [14]. In addition, it is difficult to predict the correct growth stage dates for large populations of crops and fields [15].A viable alternative for mapping evaporation at field and regional scales is the use of satellite images that can provide an excellent tool to detect the spatial and temporal structure of ET [16]. Remote sensing (RS) is a reliable and cost-effective method to forecas...
The surface energy balance algorithm for land (SEBAL) has been demonstrated to provide accurate estimates of crop evapotranspiration (ET) and yield at different spatial scales even under highly heterogeneous conditions. However, validation of the SEBAL using in-field direct and indirect measurements of plant water status is a necessary step before deploying the algorithm as an irrigation scheduling tool. To this end, a study was conducted in a maize field located near the Venice Lagoon area in Italy. The experimental area was irrigated using a 274 m long variable rate irrigation (VRI) system with 25-m sections. Three irrigation management zones (IMZs; high, medium and low irrigation requirement zones) were defined combining soil texture and normalized difference vegetation index (NDVI) data. Soil moisture sensors were installed in the different IMZs and used to schedule irrigation. In addition, SEBAL-based actual evapotranspiration (ETr) and biomass estimates were calculated throughout the season. VRI management allowed crop water demand to be matched, saving up to 42 mm (−16%) of water when compared to uniform irrigation rates. The high irrigation amounts applied during the growing season to avoid water stress resulted in no significant differences among the IMZs. SEBAL-based biomass estimates agreed with in-season measurements at 72, 105 and 112 days after planting (DAP; r2 = 0.87). Seasonal ET matched the spatial variability observed in the measured yield map at harvest. Moreover, the SEBAL-derived yield map largely agreed with the measured yield map with relative errors of 0.3% among the IMZs and of 1% (0.21 t ha-1) for the whole field. While the FAO method-based stress coefficient (Ks) never dropped below the optimum condition (Ks = 1) for all the IMZs and the uniform zone, SEBAL Ks was sensitive to changes in water status and remained below 1 during most of the growing season. Using SEBAL to capture the daily spatial variation in crop water needs and growth would enable the definition of transient, dynamic IMZs. This allows farmers to apply proper irrigation amounts increasing water use efficiency.
Water scarcity is worsened by climate change. Water savings can be reached by improving irrigation efficiency both on farm and on water supply. To do that, the choice of the best irrigation technology is not always straightforward, because farmers need to renew and implement farm infrastructures for irrigation. This study compares three irrigation systems, one drip irrigation and two sprinkler (center pivot and hose-reel) systems, on environmental, economic, and energetic performance under irrigated and non-irrigated maize cropping. The study combines impact and efficiency indicators, addressing a sustainability analysis for the irrigation practice under the three different irrigation systems. The sustainability for the irrigation systems was assessed using water-related indicators (water use efficiency, irrigation water use efficiency, and water footprint), biomass (crop growth rate, relative growth rate, harvest index, and yield response factor), and energy indicators (energy footprint, performance, and energy cost footprint) for the environmental aspect; and the economic-based indicators (water productivity and economic water footprint) for the economic aspect. Main results address the center pivot system as the best solution for irrigation practice since it demonstrated higher economic and environmental performance. Moreover, maize under the pivot system allowed a higher biomass production, economic benefits, and water use efficiency.
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